Challenges in data storage and data management in a clinical diagnostic setting

The implementation of next-generation sequencing (NGS) in a clinical diagnostic setting opens vast opportunities through the ability to sequence all genes contributing to a certain morbidity simultaneously at a cost and speed that is superior to traditional sequencing approaches. On the other hand,...

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Bibliographic Details
Published inLaboratoriumsmedizin Vol. 42; no. 6; pp. 219 - 224
Main Author Eck, Sebastian H.
Format Journal Article
LanguageEnglish
Published Berlin De Gruyter 19.12.2018
Walter de Gruyter GmbH
Subjects
Cloud computing
Data analysis
Data integration
Data management
Data processing
Data storage
Diagnostic systems
Integration
Morbidity
Next-generation sequencing
next-generation sequencing (NGS)
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Summary:The implementation of next-generation sequencing (NGS) in a clinical diagnostic setting opens vast opportunities through the ability to sequence all genes contributing to a certain morbidity simultaneously at a cost and speed that is superior to traditional sequencing approaches. On the other hand, the practical implementation of NGS in a clinical diagnostic setting involves a variety of new challenges, which need to be overcome. Among these are the generation, analysis and storage of unprecedented amounts of data, strict control of sequencing performance, validation of results, interpretation of detected variants and reporting. In the following sections, key aspects of data management and integration will be discussed. In particular, issues of data storage, data analysis using in-house IT infrastructure vs. data analysis employing cloud computing and the need for data integration from different sources will be covered.
ISSN:0342-3026
1439-0477
DOI:10.1515/labmed-2018-0054